Claudio Fantinuoli — Language Technologies — Innovation, Research & Management
I am fascinated by how minds work, how language connects us, and what happens when machines become part of that connection. My work brings together research, building software, and helping people make sense of technological change.
I created InterpretBank and Interpreter24, and I am a professor at Mainz University. These projects reflect two closely connected interests: how technology can support human expertise, and what it means when machines begin to perform the same tasks.
Alongside my own projects, I work as a C-level executive and advise companies and public institutions on AI and communication. This includes Voiseed, where we build high-quality synthetic voices, and the European Parliament. My work ranges from helping teams rethink how they work to turning ideas into working prototypes.
I write about these questions on my blog and as a technology columnist for Multilingual. The magazine named me among its 16 thought leaders shaping the future of the language industry.
You can reach me at info@fantinuoli.org.
Recent blog posts
- Beyond ‘Good Enough’: Asking the Harder Question About AI Translation
The debate about whether AI translation is good enough risks mistaking a transitional moment for the future. What happens to professional expertise if the technology becomes very good?
- Strange Times: Living Through the Great AI Divide
I have never experienced anything quite like this in my life: a divide, among genuinely intelligent, informed people, that runs this deep, this evenly, and this fast.
- End-to-end versus cascading AI interpreting
End-to-end speech translation is moving from research prototypes into usable systems. The important question is no longer whether the architecture works, but what it changes in our understanding of interpreting, control, latency and human expertise.
- Empathy: The Last Frontier
Anyone following the debate on machine interpreting knows the sequence of arguments by heart. First we were told: the machine will never be accurate enough. Interpreting is too complex, too contextual, too ambiguous for an automatic system to render faithfully. Then accuracy improved exponentially, and across many domains and language pairs the gap narrowed until,…
- The End of Translation and Interpreting Studies as we know them
People were thinking seriously about translation long before anyone thought of studying it. Cicero, defending his renderings of the Attic orators, already distinguished between translating ut interpres and ut orator — word for word, or sense for sense. Jerome wrestled with the same dilemma in his letter to Pammachius; Luther defended his German Bible against…